Whole-heartedly agree that dashboards are commoditizing the eye candy of data data data and do nothing for garbage-in-garbage-out structural deficiencies. Since products like Tableau have arrived, the marginal cost of delivering “some colorful data product” has reduced to a few committed grad students.

That said, you have also provided some solid pointers on how Gov. can better discern the nature of said data and whether there is any point dashboarding it. Here is an extended take on that involves a shameless plug of our startup non-profit :)

At ARGO Labs, we create colorful dashboards too but first try and collect the the ground truth or a dataset that comes close. GT-aaS (Ground Truthing as a Service)as I like to term it endeavors to reduce the distance between some “on the ground reality” to some operational decision made in HQ.

Consider the proverbial pothole.

Nations, states, and cities spend Billions of public $ every year going asphalt blazing on heroic pothole blitzes and allocate gargantuan sums of public $ to highway and street maintenance. (Less maintenance, more strip and mill)

Yet the ground truth (pun very much intended) that supports these $$$ is a distant reality at best, and egregiously false, at worst.

Many cities wait for enough folks to yell or complain loudly through 311 and citizen reporting apps. Dashboards are then then built on complaint data to act on what is most likely a small majority of angry or exhaustively persistent citizens. We call this the whack-a-mole approach.

Some cities are proactive in measuring all their streets but the measurements are woefully inadequate. Windshield surveying is the official term for eye-ballingstreet defects such as cracks and potholes and to generate a PCI score* to justify the expenditure of said Billions.

To remedy this subjectivity, enter the IRI or the International Roughness Index, a standard that requires that military grade hardware and lasers (pew pew) be used to measure cracks at a millimeter scale. A classic fallacy of over-engineering.The cost of this service? Upwards of $200 per mile of street just to pew pew survey and generate millimeter level data to support a simple decision.

Which streets in my city are worse of than others?

For context. Syracuse, NY has about 750 center-lane miles of streets. Using lasers works out to about $150,000 for a single survey of all streets.

NYC has between 6,000–7,000 center-lane miles of streets and would cost $1,300,000 to perform a similar survey.

We can do better and perform a good enough census of street conditions and the good news is that it’s cheap and quick!

Using a $30 computer, a $20 camera, an inexpensive but unlimited data plan, AWS, and data plumbing (2016 prices), we surveyed 520+ miles of streets in just 10 days and streamed 110,000 HD images + telemetry to the cloud. Our efforts were subsidized by a $35,000 prototyping grant from the kind folks at the Knight Foundation that kept us fed, clothed, and bills paid for 2 of us for 3 months.

Today, an app called Open Street Cam does the same for free and is open-source.

The SQUID device we used in 2016. Consisted of $100 worth of hardware components and some data plumbing.

This is what our dashboard looks like to let the City of Syracuse know where their bumpiest roads were in April 2016. This dashboard displays data about 110,000 images or 520+ miles of street.

We are getting better in measuring the ground truth. FYI: Shadows are our nemesis.

Ground Truthing as a Service — SQUID Computer Vision to pioneer a 2.0 Pavement Condition Index

*PCI = Pavement Condition Index developed by the Army Core of Engineers in the late 70s to train people in trucks to eyeball street defects according to some rubric.

Insert Michael Lewis quote for dramatic ending

People want an authority to tell them how to value things. But they chose this authority not based on facts or results. They chose it because it seems authoritative and familiar — The Big Short